#67 AlphaFold and variant effect prediction with Amelie Stein

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   E70 · 21 Dec 2023 · 52 min

   #70 Prioritizing drug target genes with Marie Sadler

   In this episode, Marie Sadler talks about her recent Cell Genomics paper, Multi-layered genetic approaches to identify approved drug targets . Previous studies have found that the drugs that target a gene linked to the disease are more likely to be approved. Yet there are many ways to define what it means for a gene to be linked to the disease. Perhaps the most straightforward approach is to rely on the genome-wide association studies (GWAS) data, but that data can also be integrated with quantitative trait loci (eQTL or pQTL) information to establish less obvious links between genetic…

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   E69 · 29 Sep 2023 · 57 min

   #69 Suffix arrays in optimal compressed space and δ-SA with Tomasz Kociumaka and Dominik Kempa

   Today on the podcast we have Tomasz Kociumaka and Dominik Kempa , the authors of the preprint Collapsing the Hierarchy of Compressed Data Structures: Suffix Arrays in Optimal Compressed Space . The suffix array is one of the foundational data structures in bioinformatics, serving as an index that allows fast substring searches in a large text. However, in its raw form, the suffix array occupies the space proportional to (and several times larger than) the original text. In their paper, Tomasz and Dominik construct a new index, δ-SA, which on the one hand can be used in the same way (answer…

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   E68 · 28 Aug 2023 · 49 min

   #68 Phylogenetic inference from raw reads and Read2Tree with David Dylus

   In this episode, David Dylus talks about Read2Tree , a tool that builds alignment matrices and phylogenetic trees from raw sequencing reads. By leveraging the database of orthologous genes called OMA , Read2Tree bypasses traditional, time-consuming steps such as genome assembly, annotation and all-versus-all sequence comparisons. Links: Inference of phylogenetic trees directly from raw sequencing reads using Read2Tree (David Dylus, Adrian Altenhoff, Sina Majidian, Fritz J. Sedlazeck, Christophe Dessimoz) Background story Read2Tree on GitHub OMA browser The Guardian’s podcast about Victoria…

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   E66 · 10 Jul 2023 · 21 min

   #66 AlphaFold and shape-mers with Janani Durairaj

   This is the second episode in the AlphaFold series, originally recorded on February 14, 2022, with Janani Durairaj , a postdoctoral researcher at the University of Basel. Janani talks about how she used shape-mers and topic modelling to discover classes of proteins assembled by AlphaFold 2 that were absent from the Protein Data Bank (PDB). The bioinformatics discussion starts at 03:35. Links: A structural biology community assessment of AlphaFold2 applications (Mehmet Akdel, Douglas E. V. Pires, Eduard Porta Pardo, Jürgen Jänes, Arthur O. Zalevsky, Bálint Mészáros, Patrick Bryant, Lydia L.…

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   E65 · 21 Jun 2023 · 52 min

   #65 AlphaFold and protein interactions with Pedro Beltrao

   In this episode, originally recorded on February 9, 2022, Roman talks to Pedro Beltrao about AlphaFold, the software developed by DeepMind that predicts a protein’s 3D structure from its amino acid sequence. Pedro is an associate professor at ETH Zurich and the coordinator of the structural biology community assessment of AlphaFold2 applications project, which involved over 30 scientists from different institutions. Pedro talks about the origins of the project, its main findings, the importance of the confidence metric that AlphaFold assigns to its predictions, and Pedro’s own area of…

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   E64 · 9 Nov 2021 · 1 hr

   #64 Enformer: predicting gene expression from sequence with Žiga Avsec

   In this episode, Jacob Schreiber interviews Žiga Avsec about a recently released model, Enformer . Their discussion begins with life differences between academia and industry, specifically about how research is conducted in the two settings. Then, they discuss the Enformer model, how it builds on previous work, and the potential that models like it have for genomics research in the future. Finally, they have a high-level discussion on the state of modern deep learning libraries and which ones they use in their day-to-day developing. Links: Effective gene expression prediction from sequence…

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   E63 · 27 Sep 2021 · 1 hr 1 min

   #63 Bioinformatics Contest 2021 with Maksym Kovalchuk and James Matthew Holt

   The Bioinformatics Contest is back this year, and we are back to discuss it! This year’s contest winners Maksym Kovalchuk (1st prize) and Matt Holt (2nd prize) talk about how they approach participating in the contest and what strategies have earned them the top scores. Timestamps and links for the individual problems: 00:10:36 Genotype Imputation 00:21:26 Causative Mutation 00:30:27 Superspreaders 00:37:22 Minor Haplotype 00:46:37 Isoform Matching Links: Matt’s solutions Max’s solutions

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   E62 · 28 Jul 2021 · 38 min

   #62 Steady states of metabolic networks and Dingo with Apostolos Chalkis

   In this episode, Apostolos Chalkis presents sampling steady states of metabolic networks as an alternative to the widely used flux balance analysis (FBA). We also discuss dingo , a Python package written by Apostolos that employs geometric random walks to sample steady states. You can see dingo in action here . Links: Dingo on GitHub Searching for COVID-19 treatments using metabolic networks Tweag open source fellowships This episode was originally published on the Compositional podcast.